Refactor: skipif for Windows 2/n (#6268)

* win

* isort

* flake8

.github/workflows/events-recurrent.yml

@@ -1,4 +1,4 @@
-name: Recurent events
+name: Recurrent events
 
 # https://jasonet.co/posts/scheduled-actions/
 # https://github.community/t/distinct-job-for-each-schedule/17811/2

pytorch_lightning/profiler/__init__.py

@@ -194,12 +194,7 @@ To visualize the profiled operation, you can either:
 
 """
 
-from pytorch_lightning.profiler.profilers import (
-    AdvancedProfiler,
-    BaseProfiler,
-    PassThroughProfiler,
-    SimpleProfiler,
-)
+from pytorch_lightning.profiler.profilers import AdvancedProfiler, BaseProfiler, PassThroughProfiler, SimpleProfiler
 from pytorch_lightning.profiler.pytorch import PyTorchProfiler
 
 __all__ = [

tests/accelerators/test_accelerator_connector.py

@@ -34,7 +34,7 @@ from pytorch_lightning.plugins import (
 from pytorch_lightning.plugins.environments import ClusterEnvironment, SLURMEnvironment, TorchElasticEnvironment
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_accelerator_choice_cpu(tmpdir):

tests/accelerators/test_ddp.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import platform
 from unittest.mock import patch
 
 import pytest
@@ -21,7 +20,7 @@ import torch
 from pytorch_lightning import Trainer
 from tests.accelerators import ddp_model, DDPLauncher
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 from tests.utilities.distributed import call_training_script
 
 CLI_ARGS = '--max_epochs 1 --gpus 2 --accelerator ddp'
@@ -83,7 +82,7 @@ def test_cli_to_pass(tmpdir, args=None):
     return '1'
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 @pytest.mark.skipif(torch.cuda.is_available(), reason="test doesn't requires GPU machine")
 def test_torch_distributed_backend_env_variables(tmpdir):
     """

tests/accelerators/test_ddp_spawn.py

@@ -20,8 +20,8 @@ from pytorch_lightning.trainer import Trainer
 from pytorch_lightning.trainer.states import TrainerState
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
-from tests.helpers.skipif import RunIf
 
 
 @RunIf(min_gpus=2)

tests/accelerators/test_dp.py

@@ -21,8 +21,8 @@ from pytorch_lightning.callbacks import EarlyStopping
 from pytorch_lightning.core import memory
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
-from tests.helpers.skipif import RunIf
 
 PRETEND_N_OF_GPUS = 16
 

tests/callbacks/test_early_stopping.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 import os
 import pickle
-import sys
 from unittest import mock
 
 import cloudpickle
@@ -27,6 +26,7 @@ from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
 
 
@@ -374,13 +374,13 @@ class EarlyStoppingModel(BoringModel):
                      3,
                      'ddp_cpu',
                      2,
-                     marks=pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")),
+                     marks=RunIf(skip_windows=True)),
         pytest.param([EarlyStopping(monitor='cba', patience=3),
                       EarlyStopping(monitor='abc')],
                      3,
                      'ddp_cpu',
                      2,
-                     marks=pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")),
+                     marks=RunIf(skip_windows=True)),
     ],
 )
 def test_multiple_early_stopping_callbacks(callbacks, expected_stop_epoch, accelerator, num_processes, tmpdir):

tests/callbacks/test_gpu_stats_monitor.py

@@ -24,7 +24,7 @@ from pytorch_lightning.loggers.csv_logs import ExperimentWriter
 from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @RunIf(min_gpus=1)

tests/callbacks/test_pruning.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import platform
 from collections import OrderedDict
 from logging import INFO
 from unittest import mock
@@ -27,7 +26,7 @@ from pytorch_lightning import seed_everything, Trainer
 from pytorch_lightning.callbacks import ModelPruning
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class TestModel(BoringModel):
@@ -169,13 +168,12 @@ def test_pruning_callback_ddp(tmpdir, use_global_unstructured, parameters_to_pru
     )
 
 
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=2, skip_windows=True)
 def test_pruning_callback_ddp_spawn(tmpdir):
     train_with_pruning_callback(tmpdir, use_global_unstructured=True, accelerator="ddp_spawn", gpus=2)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_pruning_callback_ddp_cpu(tmpdir):
     train_with_pruning_callback(tmpdir, parameters_to_prune=True, accelerator="ddp_cpu", num_processes=2)
 

tests/callbacks/test_quantization.py

@@ -21,8 +21,8 @@ from pytorch_lightning.callbacks import QuantizationAwareTraining
 from pytorch_lightning.metrics.functional.mean_relative_error import mean_relative_error
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.datamodules import RegressDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import RegressionModel
-from tests.helpers.skipif import RunIf
 
 
 @pytest.mark.parametrize("observe", ['average', pytest.param('histogram', marks=RunIf(min_torch="1.5"))])

tests/callbacks/test_stochastic_weight_avg.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import platform
 from unittest import mock
 
 import pytest
@@ -24,7 +23,7 @@ from pytorch_lightning import Trainer
 from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_6
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel, RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 if _TORCH_GREATER_EQUAL_1_6:
     from pytorch_lightning.callbacks import StochasticWeightAveraging
@@ -128,8 +127,7 @@ def test_swa_callback_ddp_spawn(tmpdir):
     train_with_swa(tmpdir, accelerator="ddp_spawn", gpus=2)
 
 
-@RunIf(min_torch="1.6.0")
-@pytest.mark.skipif(platform.system() == "Windows", reason="ddp_cpu is not available on Windows")
+@RunIf(min_torch="1.6.0", skip_windows=True)
 def test_swa_callback_ddp_cpu(tmpdir):
     train_with_swa(tmpdir, accelerator="ddp_cpu", num_processes=2)
 

tests/checkpointing/test_torch_saving.py

@@ -12,14 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import platform
 
-import pytest
 import torch
 
 from pytorch_lightning import Trainer
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_model_torch_save(tmpdir):
@@ -39,7 +37,7 @@ def test_model_torch_save(tmpdir):
     trainer = torch.load(temp_path)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_model_torch_save_ddp_cpu(tmpdir):
     """Test to ensure torch save does not fail for model and trainer using cpu ddp."""
     model = BoringModel()

tests/core/test_datamodules.py

@@ -26,8 +26,8 @@ from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from tests.helpers import BoringDataModule, BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
-from tests.helpers.skipif import RunIf
 from tests.helpers.utils import reset_seed, set_random_master_port
 
 

tests/core/test_decorators.py

@@ -16,7 +16,7 @@ import torch
 
 from pytorch_lightning.core.decorators import auto_move_data
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @RunIf(min_gpus=1)

tests/core/test_memory.py

@@ -21,7 +21,7 @@ from pytorch_lightning.utilities import _NATIVE_AMP_AVAILABLE
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.advanced_models import ParityModuleRNN
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class EmptyModule(LightningModule):

tests/core/test_metric_result_integration.py

@@ -11,9 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import sys
 
-import pytest
 import torch
 import torch.distributed as dist
 import torch.multiprocessing as mp
@@ -21,6 +19,7 @@ import torch.multiprocessing as mp
 import tests.helpers.utils as tutils
 from pytorch_lightning.core.step_result import Result
 from pytorch_lightning.metrics import Metric
+from tests.helpers.runif import RunIf
 
 
 class DummyMetric(Metric):
@@ -90,7 +89,7 @@ def _ddp_test_fn(rank, worldsize):
             assert epoch_expected[k] == epoch_log[k]
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(skip_windows=True)
 def test_result_reduce_ddp():
     """Make sure result logging works with DDP"""
     tutils.reset_seed()

tests/core/test_results.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import random
-import sys
 from pathlib import Path
 
 import pytest
@@ -26,7 +25,7 @@ from pytorch_lightning import Trainer
 from pytorch_lightning.core.step_result import Result
 from pytorch_lightning.trainer.states import TrainerState
 from tests.helpers import BoringDataModule, BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def _setup_ddp(rank, worldsize):
@@ -49,7 +48,7 @@ def _ddp_test_fn(rank, worldsize, result_cls: Result):
 
 
 @pytest.mark.parametrize("result_cls", [Result])
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(skip_windows=True)
 def test_result_reduce_ddp(result_cls):
     """Make sure result logging works with DDP"""
     tutils.reset_seed()

tests/deprecated_api/test_remove_1-4.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Test deprecated functionality which will be removed in v1.4.0"""
-import sys
 
 import pytest
 import torch
@@ -28,7 +27,7 @@ from pytorch_lightning.plugins import DDPSpawnPlugin
 from pytorch_lightning.plugins.environments import TorchElasticEnvironment
 from tests.deprecated_api import _soft_unimport_module
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_v1_4_0_deprecated_trainer_attributes():
@@ -178,8 +177,7 @@ class CustomDDPPlugin(DDPSpawnPlugin):
             assert isinstance(self.model.module, LightningDistributedModule)
 
 
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(min_gpus=2, skip_windows=True)
 def test_v1_4_0_deprecated_lightning_distributed_data_parallel(tmpdir):
     model = BoringModel()
     trainer = Trainer(

tests/helpers/runif.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+import sys
 from distutils.version import LooseVersion
 from typing import Optional
 
@@ -31,13 +32,22 @@ class RunIf:
             assert arg1 > 0.0
     """
 
-    def __new__(self, *args, min_gpus: int = 0, min_torch: Optional[str] = None, quantization: bool = False, **kwargs):
+    def __new__(
+        self,
+        *args,
+        min_gpus: int = 0,
+        min_torch: Optional[str] = None,
+        quantization: bool = False,
+        skip_windows: bool = False,
+        **kwargs
+    ):
         """
         Args:
             args: native pytest.mark.skipif arguments
             min_gpus: min number of gpus required to run test
             min_torch: minimum pytorch version to run test
             quantization: if `torch.quantization` package is required to run test
+            skip_windows: skip test for Windows platform (typically fo some limited torch functionality)
             kwargs: native pytest.mark.skipif keyword arguments
         """
         conditions = []
@@ -57,6 +67,10 @@ class RunIf:
             conditions.append(not _TORCH_QUANTIZE_AVAILABLE or _miss_default)
             reasons.append("missing PyTorch quantization")
 
+        if skip_windows:
+            conditions.append(sys.platform == "win32")
+            reasons.append("unimplemented on Windows")
+
         reasons = [rs for cond, rs in zip(conditions, reasons) if cond]
         return pytest.mark.skipif(
             *args,

tests/loggers/test_all.py

@@ -14,7 +14,6 @@
 import inspect
 import os
 import pickle
-import platform
 from unittest import mock
 from unittest.mock import ANY
 
@@ -34,6 +33,7 @@ from pytorch_lightning.loggers import (
 from pytorch_lightning.loggers.base import DummyExperiment
 from pytorch_lightning.trainer.states import TrainerState
 from tests.helpers import BoringModel
+from tests.helpers.runif import RunIf
 from tests.loggers.test_comet import _patch_comet_atexit
 from tests.loggers.test_mlflow import mock_mlflow_run_creation
 
@@ -332,7 +332,7 @@ class RankZeroLoggerCheck(Callback):
         TestTubeLogger,
     ]
 )
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_logger_created_on_rank_zero_only(tmpdir, monkeypatch, logger_class):
     """ Test that loggers get replaced by dummy loggers on global rank > 0"""
     _patch_comet_atexit(monkeypatch)

tests/metrics/test_composition.py

@@ -18,7 +18,7 @@ import torch
 
 from pytorch_lightning.metrics.compositional import CompositionalMetric
 from pytorch_lightning.metrics.metric import Metric
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class DummyMetric(Metric):

tests/metrics/test_ddp.py

@@ -1,9 +1,8 @@
-import sys
-
 import pytest
 import torch
 
 from pytorch_lightning.metrics import Metric
+from tests.helpers.runif import RunIf
 from tests.metrics.test_metric import Dummy
 from tests.metrics.utils import setup_ddp
 
@@ -40,7 +39,7 @@ def _test_ddp_sum_cat(rank, worldsize):
     assert dummy.bar == worldsize
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(skip_windows=True)
 @pytest.mark.parametrize("process", [_test_ddp_cat, _test_ddp_sum, _test_ddp_sum_cat])
 def test_ddp(process):
     torch.multiprocessing.spawn(process, args=(2, ), nprocs=2)
@@ -66,7 +65,7 @@ def _test_non_contiguous_tensors(rank, worldsize):
     metric.update(torch.randn(10, 5)[:, 0])
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(skip_windows=True)
 def test_non_contiguous_tensors():
     """ Test that gather_all operation works for non contiguous tensors """
     torch.multiprocessing.spawn(_test_non_contiguous_tensors, args=(2, ), nprocs=2)

tests/metrics/test_metric.py

@@ -9,7 +9,7 @@ import torch
 from torch import nn
 
 from pytorch_lightning.metrics.metric import Metric, MetricCollection
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 torch.manual_seed(42)
 

tests/models/test_amp.py

@@ -25,7 +25,7 @@ from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities import _APEX_AVAILABLE
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class AMPTestModel(BoringModel):

tests/models/test_cpu.py

@@ -12,9 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import platform
 
-import pytest
 import torch
 
 import tests.helpers.pipelines as tpipes
@@ -24,6 +22,7 @@ from pytorch_lightning.callbacks import Callback, EarlyStopping, ModelCheckpoint
 from pytorch_lightning.trainer.states import TrainerState
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
 
 
@@ -126,7 +125,7 @@ def test_early_stopping_cpu_model(tmpdir):
     model.unfreeze()
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_multi_cpu_model_ddp(tmpdir):
     """Make sure DDP works."""
     tutils.set_random_master_port()

tests/models/test_gpu.py

@@ -25,8 +25,8 @@ from pytorch_lightning.utilities import device_parser
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
-from tests.helpers.skipif import RunIf
 
 PRETEND_N_OF_GPUS = 16
 

tests/models/test_hooks.py

@@ -22,7 +22,7 @@ import torch
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.trainer.states import TrainerState
 from tests.helpers import BoringModel, RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.mark.parametrize('max_steps', [1, 2, 3])

tests/models/test_horovod.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 import json
 import os
-import platform
 import shlex
 import subprocess
 import sys
@@ -32,7 +31,7 @@ from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities import _APEX_AVAILABLE, _HOROVOD_AVAILABLE, _NATIVE_AMP_AVAILABLE
 from tests.helpers import BoringModel
 from tests.helpers.advanced_models import BasicGAN
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 if _HOROVOD_AVAILABLE:
     import horovod
@@ -67,7 +66,7 @@ def _run_horovod(trainer_options, on_gpu=False):
     assert exit_code == 0
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_horovod_cpu(tmpdir):
     """Test Horovod running multi-process on CPU."""
     trainer_options = dict(
@@ -84,7 +83,7 @@ def test_horovod_cpu(tmpdir):
     _run_horovod(trainer_options)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_horovod_cpu_implicit(tmpdir):
     """Test Horovod without specifying a backend, inferring from env set by `horovodrun`."""
     trainer_options = dict(
@@ -100,9 +99,8 @@ def test_horovod_cpu_implicit(tmpdir):
     _run_horovod(trainer_options)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
 @pytest.mark.skipif(not _HOROVOD_NCCL_AVAILABLE, reason="test requires Horovod with NCCL support")
-@RunIf(min_gpus=2)
+@RunIf(min_gpus=2, skip_windows=True)
 def test_horovod_multi_gpu(tmpdir):
     """Test Horovod with multi-GPU support."""
     trainer_options = dict(
@@ -121,9 +119,8 @@ def test_horovod_multi_gpu(tmpdir):
 
 
 @pytest.mark.skip(reason="Horovod has a problem with broadcast when using apex?")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
 @pytest.mark.skipif(not _HOROVOD_NCCL_AVAILABLE, reason="test requires Horovod with NCCL support")
-@RunIf(min_gpus=2)
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(not _APEX_AVAILABLE, reason="test requires apex")
 def test_horovod_apex(tmpdir):
     """Test Horovod with multi-GPU support using apex amp."""
@@ -145,9 +142,8 @@ def test_horovod_apex(tmpdir):
 
 
 @pytest.mark.skip(reason="Skip till Horovod fixes integration with Native torch.cuda.amp")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
 @pytest.mark.skipif(not _HOROVOD_NCCL_AVAILABLE, reason="test requires Horovod with NCCL support")
-@RunIf(min_gpus=2)
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(not _NATIVE_AMP_AVAILABLE, reason="test requires torch.cuda.amp")
 def test_horovod_amp(tmpdir):
     """Test Horovod with multi-GPU support using native amp."""
@@ -168,9 +164,8 @@ def test_horovod_amp(tmpdir):
     _run_horovod(trainer_options, on_gpu=True)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
 @pytest.mark.skipif(not _HOROVOD_NCCL_AVAILABLE, reason="test requires Horovod with NCCL support")
-@RunIf(min_gpus=1)
+@RunIf(min_gpus=1, skip_windows=True)
 def test_horovod_transfer_batch_to_gpu(tmpdir):
 
     class TestTrainingStepModel(BoringModel):
@@ -198,7 +193,7 @@ def test_horovod_transfer_batch_to_gpu(tmpdir):
     tpipes.run_model_test_without_loggers(trainer_options, model)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_horovod_multi_optimizer(tmpdir):
     model = BasicGAN()
 
@@ -233,7 +228,7 @@ def test_horovod_multi_optimizer(tmpdir):
 # TODO: unclear Horovod failure...
 @pytest.mark.skip(reason="unclear Horovod failure...")
 @pytest.mark.skipif(not _HOROVOD_AVAILABLE, reason="Horovod is unavailable")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_result_reduce_horovod(tmpdir):
     """Make sure result logging works with Horovod.
 
@@ -284,7 +279,7 @@ def test_result_reduce_horovod(tmpdir):
 # TODO: unclear Horovod failure...
 @pytest.mark.skip(reason="unclear Horovod failure...")
 @pytest.mark.skipif(not _HOROVOD_AVAILABLE, reason="Horovod is unavailable")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_accuracy_metric_horovod():
     num_batches = 10
     batch_size = 16
@@ -335,7 +330,7 @@ def test_accuracy_metric_horovod():
     horovod.run(_compute_batch, np=2)
 
 
-# @pytest.mark.skipif(platform.system() == "Windows", reason="Horovod is not supported on Windows")
+# @RunIf(skip_windows=True)
 # def test_horovod_multi_optimizer_with_scheduling_stepping(tmpdir):
 #     model = BoringModel()
 #     model.configure_optimizers = model.configure_optimizers__multiple_schedulers

tests/models/test_onnx.py

@@ -22,7 +22,7 @@ import tests.helpers.pipelines as tpipes
 import tests.helpers.utils as tutils
 from pytorch_lightning import Trainer
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_model_saves_with_input_sample(tmpdir):

tests/models/test_restore.py

@@ -30,8 +30,8 @@ from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.trainer.states import RunningStage, TrainerState
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
+from tests.helpers.runif import RunIf
 from tests.helpers.simple_models import ClassificationModel
-from tests.helpers.skipif import RunIf
 
 
 class ModelTrainerPropertyParity(Callback):

tests/models/test_sync_batchnorm.py

@@ -24,7 +24,7 @@ from pytorch_lightning.plugins.environments import TorchElasticEnvironment
 from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities import FLOAT16_EPSILON
 from tests.helpers.datamodules import MNISTDataModule
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 from tests.helpers.utils import set_random_master_port
 
 

tests/models/test_torchscript.py

@@ -19,7 +19,7 @@ import torch
 from tests.helpers import BoringModel
 from tests.helpers.advanced_models import BasicGAN, ParityModuleRNN
 from tests.helpers.datamodules import MNISTDataModule
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.mark.parametrize("modelclass", [

tests/overrides/test_data_parallel.py

@@ -13,7 +13,7 @@ from pytorch_lightning.overrides.data_parallel import (
 )
 from pytorch_lightning.trainer.states import RunningStage
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.mark.parametrize("wrapper_class", [

tests/plugins/test_amp_plugin.py

@@ -8,7 +8,7 @@ from pytorch_lightning import Trainer
 from pytorch_lightning.plugins import NativeMixedPrecisionPlugin
 from pytorch_lightning.utilities import _NATIVE_AMP_AVAILABLE
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.mark.skipif(not _NATIVE_AMP_AVAILABLE, reason="Minimal PT version is set to 1.6")

tests/plugins/test_deepspeed_plugin.py

@@ -12,7 +12,7 @@ from pytorch_lightning.plugins.training_type.deepspeed import LightningDeepSpeed
 from pytorch_lightning.utilities import _APEX_AVAILABLE, _DEEPSPEED_AVAILABLE, _NATIVE_AMP_AVAILABLE
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_deepspeed_lightning_module(tmpdir):

tests/plugins/test_rpc_plugin.py

@@ -9,7 +9,7 @@ from pytorch_lightning.callbacks import Callback
 from pytorch_lightning.plugins.training_type.rpc_sequential import RPCPlugin
 from pytorch_lightning.utilities import _RPC_AVAILABLE
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @mock.patch.dict(

tests/plugins/test_rpc_sequential_plugin.py

@@ -24,7 +24,7 @@ from pytorch_lightning.plugins.training_type.rpc_sequential import RPCSequential
 from pytorch_lightning.utilities import _FAIRSCALE_PIPE_AVAILABLE
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.boring_model import RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.mark.skipif(not _FAIRSCALE_PIPE_AVAILABLE, reason="test requires FairScale to be installed")

tests/plugins/test_sharded_plugin.py

@@ -1,5 +1,4 @@
 import os
-import platform
 
 import pytest
 import torch
@@ -10,7 +9,7 @@ from pytorch_lightning.plugins import DDPShardedPlugin, DDPSpawnShardedPlugin
 from pytorch_lightning.utilities import _APEX_AVAILABLE, _FAIRSCALE_AVAILABLE, _NATIVE_AMP_AVAILABLE
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.mark.parametrize(["accelerator"], [("ddp_sharded", ), ("ddp_sharded_spawn", )])
@@ -90,7 +89,7 @@ def test_ddp_choice_sharded_amp(tmpdir, accelerator):
         trainer.fit(model)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_checkpoint_cpu(tmpdir):
     """
@@ -114,8 +113,7 @@ def test_ddp_sharded_plugin_checkpoint_cpu(tmpdir):
         assert torch.equal(ddp_param.to("cpu"), shard_param)
 
 
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_checkpoint_multi_gpu(tmpdir):
     """
@@ -139,8 +137,7 @@ def test_ddp_sharded_plugin_checkpoint_multi_gpu(tmpdir):
         assert torch.equal(ddp_param.to("cpu"), shard_param)
 
 
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_finetune(tmpdir):
     """
@@ -162,7 +159,7 @@ def test_ddp_sharded_plugin_finetune(tmpdir):
     trainer.fit(saved_model)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_resume_from_checkpoint(tmpdir):
     """
@@ -194,8 +191,7 @@ def test_ddp_sharded_plugin_resume_from_checkpoint(tmpdir):
 
 @pytest.mark.skip(reason="Not a critical test, skip till drone CI performance improves.")
 @pytest.mark.skip(reason="Currently unsupported restarting training on different number of devices.")
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_resume_from_checkpoint_downsize_gpus(tmpdir):
     """
@@ -225,8 +221,7 @@ def test_ddp_sharded_plugin_resume_from_checkpoint_downsize_gpus(tmpdir):
     trainer.fit(model)
 
 
-@RunIf(min_gpus=1)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=1, skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_resume_from_checkpoint_gpu_to_cpu(tmpdir):
     """
@@ -256,7 +251,7 @@ def test_ddp_sharded_plugin_resume_from_checkpoint_gpu_to_cpu(tmpdir):
     trainer.fit(model)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 @pytest.mark.skipif(
     not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
@@ -275,8 +270,7 @@ def test_ddp_sharded_plugin_test(tmpdir):
     trainer.test(model)
 
 
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 def test_ddp_sharded_plugin_test_multigpu(tmpdir):
     """

tests/trainer/legacy_deprecate_flow_log/test_trainer_steps_scalar_return.py

@@ -22,7 +22,7 @@ import torch
 from pytorch_lightning import Trainer
 from tests.helpers import BoringModel
 from tests.helpers.deterministic_model import DeterministicModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_training_step_scalar(tmpdir):

tests/trainer/logging_/test_distributed_logging.py

@@ -12,14 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import platform
 from unittest import mock
 
-import pytest
-
 from pytorch_lightning import Trainer
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class TestModel(BoringModel):
@@ -33,7 +30,7 @@ class TestModel(BoringModel):
             assert logged_times == expected, msg
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 def test_global_zero_only_logging_ddp_cpu(tmpdir):
     """
     Makes sure logging only happens from root zero

tests/trainer/logging_/test_logger_connector.py

@@ -29,7 +29,7 @@ from pytorch_lightning.trainer.connectors.logger_connector.callback_hook_validat
 from pytorch_lightning.trainer.connectors.logger_connector.metrics_holder import MetricsHolder
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.boring_model import BoringModel, RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def decorator_with_arguments(fx_name: str = '', hook_fx_name: str = None) -> Callable:

tests/trainer/logging_/test_train_loop_logging_1_0.py

@@ -31,7 +31,7 @@ from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
 from pytorch_lightning.core.lightning import LightningModule
 from tests.helpers.boring_model import BoringModel, RandomDictDataset, RandomDictStringDataset
 from tests.helpers.deterministic_model import DeterministicModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @mock.patch.dict(os.environ, {"PL_DEV_DEBUG": "1"})

tests/trainer/optimization/test_manual_optimization.py

@@ -26,7 +26,7 @@ from pytorch_lightning import seed_everything, Trainer
 from pytorch_lightning.callbacks import Callback
 from pytorch_lightning.utilities import _APEX_AVAILABLE
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @mock.patch.dict(os.environ, {"PL_DEV_DEBUG": "1"})

tests/trainer/properties/test_get_model.py

@@ -11,14 +11,11 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import sys
-
-import pytest
 
 from pytorch_lightning import Trainer
 from tests.accelerators import DDPLauncher
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class TrainerGetModel(BoringModel):
@@ -47,7 +44,7 @@ def test_get_model(tmpdir):
     trainer.fit(model)
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(skip_windows=True)
 def test_get_model_ddp_cpu(tmpdir):
     """
     Tests that `trainer.lightning_module` extracts the model correctly when using ddp on cpu
@@ -86,8 +83,7 @@ def test_get_model_gpu(tmpdir):
     trainer.fit(model)
 
 
-@RunIf(min_gpus=1)
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(min_gpus=1, skip_windows=True)
 @DDPLauncher.run("--accelerator [accelerator]", max_epochs=["1"], accelerator=["ddp", "ddp_spawn"])
 def test_get_model_ddp_gpu(tmpdir, args=None):
     """

tests/trainer/test_data_loading.py

@@ -20,7 +20,7 @@ from torch.utils.data.sampler import BatchSampler, SequentialSampler
 from pytorch_lightning import Trainer
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel, RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class IndexedRandomDataset(RandomDataset):

tests/trainer/test_dataloaders.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-import platform
 from unittest import mock
 from unittest.mock import patch
 
@@ -30,7 +29,7 @@ from pytorch_lightning.utilities.data import has_iterable_dataset, has_len
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.base import EvalModelTemplate
 from tests.helpers.boring_model import BoringModel, RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_fit_train_loader_only(tmpdir):
@@ -600,7 +599,7 @@ def test_error_on_zero_len_dataloader(tmpdir):
         trainer.fit(model)
 
 
-@pytest.mark.skipif(platform.system() == 'Windows', reason='Does not apply to Windows platform.')
+@RunIf(skip_windows=True)
 @pytest.mark.parametrize('ckpt_path', [None, 'best', 'specific'])
 @patch('pytorch_lightning.trainer.data_loading.multiprocessing.cpu_count', return_value=4)
 def test_warning_with_few_workers(mock, tmpdir, ckpt_path):
@@ -646,7 +645,7 @@ def test_warning_with_few_workers(mock, tmpdir, ckpt_path):
         trainer.test(**test_options)
 
 
-@pytest.mark.skipif(platform.system() == 'Windows', reason='Does not apply to Windows platform.')
+@RunIf(skip_windows=True)
 @pytest.mark.parametrize('ckpt_path', [None, 'best', 'specific'])
 @patch('pytorch_lightning.trainer.data_loading.multiprocessing.cpu_count', return_value=4)
 def test_warning_with_few_workers_multi_loader(mock, tmpdir, ckpt_path):
@@ -808,8 +807,7 @@ class DistribSamplerCallback(Callback):
         assert not test_sampler.shuffle
 
 
-@pytest.mark.skipif(platform.system() == 'Windows', reason='Does not apply to Windows platform.')
-@RunIf(min_gpus=2)
+@RunIf(min_gpus=2, skip_windows=True)
 def test_dataloader_distributed_sampler(tmpdir):
     """ Test DistributedSampler and it's arguments for DDP backend """
 
@@ -836,8 +834,7 @@ class ModelWithDataLoaderDistributedSampler(EvalModelTemplate):
         )
 
 
-@pytest.mark.skipif(platform.system() == 'Windows', reason='Does not apply to Windows platform.')
-@RunIf(min_gpus=2)
+@RunIf(min_gpus=2, skip_windows=True)
 def test_dataloader_distributed_sampler_already_attached(tmpdir):
     """ Test DistributedSampler and it's arguments for DDP backend when DistSampler already included on dataloader """
 

tests/trainer/test_trainer.py

@@ -14,7 +14,6 @@
 import math
 import os
 import pickle
-import platform
 import sys
 from argparse import Namespace
 from copy import deepcopy
@@ -42,7 +41,7 @@ from pytorch_lightning.utilities.cloud_io import load as pl_load
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.base import EvalModelTemplate
 from tests.helpers import BoringModel, RandomDataset
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @pytest.fixture
@@ -221,8 +220,14 @@ def test_trainer_accumulate_grad_batches_zero_grad(tmpdir, accumulate_grad_batch
 @pytest.mark.parametrize(
     ["accumulate_grad_batches", "limit_train_batches"],
     [
-        ({1: 2, 3: 4}, 1.0),
-        ({1: 2, 3: 4}, 0.5),  # not to be divisible by accumulate_grad_batches on purpose
+        ({
+            1: 2,
+            3: 4
+        }, 1.0),
+        ({
+            1: 2,
+            3: 4
+        }, 0.5),  # not to be divisible by accumulate_grad_batches on purpose
         (3, 1.0),
         (3, 0.8),  # not to be divisible by accumulate_grad_batches on purpose
         (4, 1.0),
@@ -1436,8 +1441,7 @@ def test_trainer_predict_ddp(tmpdir):
     predict(tmpdir, "ddp", 2, None, plugins=["ddp_sharded"])
 
 
-@RunIf(min_gpus=2)
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(
     not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
 )
@@ -1453,7 +1457,7 @@ def test_trainer_predict_1_gpu(tmpdir):
     predict(tmpdir, None, 1, None)
 
 
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
+@RunIf(skip_windows=True)
 @pytest.mark.skipif(
     not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
 )

tests/trainer/test_trainer_cli.py

@@ -22,7 +22,7 @@ import pytest
 import tests.helpers.utils as tutils
 from pytorch_lightning import Trainer
 from pytorch_lightning.utilities import argparse
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @mock.patch('argparse.ArgumentParser.parse_args')

tests/trainer/test_trainer_test_loop.py

@@ -16,7 +16,7 @@ import torch
 import pytorch_lightning as pl
 import tests.helpers.utils as tutils
 from tests.base import EvalModelTemplate
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @RunIf(min_gpus=2)

tests/trainer/test_trainer_tricks.py

@@ -25,7 +25,7 @@ from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.base import EvalModelTemplate
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import MNISTDataModule
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def test_num_training_batches(tmpdir):

tests/tuner/test_auto_gpu_select.py

@@ -19,7 +19,7 @@ import torch
 from pytorch_lightning import Trainer
 from pytorch_lightning.tuner.auto_gpu_select import pick_multiple_gpus
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 @RunIf(min_gpus=2)

tests/utilities/test_all_gather_grad.py

@@ -8,7 +8,7 @@ import torch
 from pytorch_lightning import seed_everything, Trainer
 from pytorch_lightning.utilities import AllGatherGrad
 from tests.helpers.boring_model import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def setup_ddp(rank, world_size):
@@ -42,14 +42,13 @@ def _test_all_gather_ddp(rank, world_size):
     assert torch.allclose(grad2, tensor2.grad)
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
+@RunIf(skip_windows=True)
 def test_all_gather_ddp():
     world_size = 3
     torch.multiprocessing.spawn(_test_all_gather_ddp, args=(world_size, ), nprocs=world_size)
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="DDP not available on windows")
-@RunIf(min_gpus=2)
+@RunIf(min_gpus=2, skip_windows=True)
 @pytest.mark.skipif(
     not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
 )

tests/utilities/test_apply_func_torchtext.py

@@ -17,7 +17,7 @@ import torchtext
 from torchtext.data.example import Example
 
 from pytorch_lightning.utilities.apply_func import move_data_to_device
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 def _get_torchtext_data_iterator(include_lengths=False):

tests/utilities/test_dtype_device_mixin.py

@@ -18,7 +18,7 @@ import torch.nn as nn
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.utilities.device_dtype_mixin import DeviceDtypeModuleMixin
 from tests.helpers import BoringModel
-from tests.helpers.skipif import RunIf
+from tests.helpers.runif import RunIf
 
 
 class SubSubModule(DeviceDtypeModuleMixin):